A regional financial-services company wanted to protect valuable customer relationships while keeping credit and service decisions responsible. Churn risk, relationship value, responsiveness to an offer and capacity to serve were being treated as if they were the same question. Marketways separated those questions and connected them in a coordinated retention and service programme.
The engagement objective
Through the initial discovery, Marketways defined the objective: coordinate retention, credit and service treatments around relationship economics.
How Marketways translated the problem
We began with a practical question: Which customers are at risk, why, and what response is worthwhile? The first analysis used transactions, products, interactions, complaints, tenure and campaign response.
That evidence could not be read in isolation. Propensity to leave, value at risk and responsiveness to an offer are different questions. Historical outcomes may reflect past policy and unequal access rather than underlying ability alone.
The customers most likely to respond were not necessarily those for whom an intervention created value. We separated prediction from causal interpretation before connecting commercial action to responsible risk.
We did not judge each component by its isolated KPI. We examined how people, assets, decisions and constraints affected one another, then used the evidence to test whether an apparent improvement would strengthen the complete system or merely move cost, pressure or risk elsewhere.
How the engagement developed
The initial work on customer churn and relationship value exposed dependencies with credit and collections decision review, branch, contact-centre and digital capacity. Treating them as separate recommendations would have left the operating trade-offs unresolved.
- Customer churn and relationship value: Focus retention action on relationships where intervention can create value.
- Credit and collections decision review: Improve risk-adjusted approval and recovery decisions.
- Branch, contact-centre and digital capacity: Reduce avoidable waiting and preserve support for complex needs.
Evidence we examined
- Transactions, products, interactions, complaints, tenure and campaign response.
- Applications, bureau data, cash flow, repayment, treatment and outcomes.
- Visits, calls, digital journeys, handling time, abandonment and staffing.
Industry conditions we accounted for
- Propensity to leave, value at risk and responsiveness to an offer are different questions.
- Historical outcomes may reflect past policy and unequal access rather than underlying ability alone.
- Digital adoption does not remove demand; it changes contact reasons and escalation patterns.
How our engagement contributed to business impact
We connected every method to a decision and a business measure. The organisation could assess the engagement through operating results as well as model performance.
- Customer churn and relationship value
- Method: Machine Learning & Predictive Analytics, Market, Customer & Behavioural Analytics.
- Evidence: Transactions, products, interactions, complaints, tenure and campaign response.
- Decision supported: Focus retention action on relationships where intervention can create value.
- Impact measure: Incremental retention, relationship value and contact cost.
- Credit and collections decision review
- Method: Statistics & Econometrics, Machine Learning & Predictive Analytics.
- Evidence: Applications, bureau data, cash flow, repayment, treatment and outcomes.
- Decision supported: Improve risk-adjusted approval and recovery decisions.
- Impact measure: Risk-adjusted return, cure rate, fairness and decision stability.
- Branch, contact-centre and digital capacity
- Method: Forecasting, Risk & Optimisation, Process, Workflow & Systems.
- Evidence: Visits, calls, digital journeys, handling time, abandonment and staffing.
- Decision supported: Reduce avoidable waiting and preserve support for complex needs.
- Impact measure: Completion, waiting, first-contact resolution and cost to serve.
Implementation
The engagement was structured as initial diagnostic and treatment trials. We connected the analysis to the decisions, operating constraints and measures that the organisation would continue to use.
How success was assessed
The overall assessment considered incremental value, fair treatment and sustainable service cost. The supporting measures included:
- Incremental retention, relationship value and contact cost.
- Risk-adjusted return, cure rate, fairness and decision stability.
- Completion, waiting, first-contact resolution and cost to serve.
Services and methods used
Services: Customer Satisfaction & Experience Research, Operational Performance Diagnostic, Decision Assurance, AI & Model Risk, Workforce Planning & Capacity, Process & Workflow Analysis & Redesign.
Methods: Machine Learning & Predictive Analytics, Market, Customer & Behavioural Analytics, Statistics & Econometrics, Forecasting, Risk & Optimisation, Process, Workflow & Systems.